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to understand, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster networking, enable internationalization and
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Ref.: 532299 Work type: Full-time Department: Hong Kong Institute for the Humanities and Social Sciences (45400) Categories: Senior Research Staff & Post-doctoral Fellow Applications are invited
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and other world leading institutes to carry out pioneering research that benefits society and changes the world around us. Our world-class researchers are driven by a passion and commitment to leaving a
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science, e.g, by leading to more effective batteries. The Research Assistant/Associate will join the Machine Learning Group at the Department of Engineering, working with Prof. José Miguel Hernández Lobato
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description This project addresses the effective design of a military supply logistics network, composed of transportation and communication links such as roads and rail, aerial drone routes, and nodes, such as
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represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster networking, enable internationalization and
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2025 Reference: RD-PHD-02-LS-MH-25 Project Title: Dietary strategies to reduce methane production in dairy cows and their effects on the rumen microbiome and metabolism Primary supervisor: Prof. Liam
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candidates who are interested in joining our team as PhD fellow. The position is available from October 1, 2025, or as soon as possible thereafter. The Ravnskjaer lab is headed by Assoc. Prof. Kim Ravnskjaer
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operational employment. This doctoral research will thus leverage the power of graph neural networks – a novel ML architecture, capable of learning fundamental physical behaviour by modelling systems as graphs